Ensuring that AI Does What We Need It to Do

I recently did an interview with Popular Science on where medical imaging started and where it is going. It is no secret that artificial intelligence (AI) will serve a role in that future.

I told the reporter that “I am excited about the day where artificial intelligence will see something in an image that we humans cannot see.” Focusing on the ability of AI to do what human eyes cannot, such as predicting which tumors will respond to therapy and which will not or developing algorithms that will help radiologists find diseases before they cause symptoms, will help radiologists provide more and more value to our patients.

As we describe how AI will be valuable in assisting radiologists and other physicians provide better care for our patients, sometimes we have to compete with those, especially in the lay press, who see AI as a tool that has an ultimate goal of replacing physicians including radiologists. Of course, nothing could be further from the truth, but we still have important education to do as the hyperbole and over-promising that is rampant in the lay press and to some degree this article to ensure the public’s expectations for AI in health care are realistic. However, I do look forward to that day AI will be able to help us “see” the things we cannot – because if the tools to help us can’t help us spot things we could not before, why have them?

To reach that point, we have to make sure AI tools are designed to do what we need them to do. That is what the ACR Data Science Institute™ (ACR DSI) is doing.

The ACR DSI will co-sponsor an August 23–24 workshop on AI in Medical Imaging, along with the National Institute of Biomedical Imaging and Bioengineering (NIBIB) and others. The proceedings will be published as a research roadmap for health professionals in academia, industry and government.

The response to the workshop has been so great that in-person attendance capacity was reached within hours of the event’s announcement. However, you can watch both days live on the internet.

Recently, the ACR DSI released its first use cases to industry leaders for comment. Use cases are clinical scenarios in which AI may improve care. These landmark ACR DSI use cases will be universally available this fall.

This is huge. Assisting developers create algorithms that answer relevant clinical questions and improve in radiology and radiation oncology is a major goal of the ACR DSI.

Many seminal steps are being taken that will impact radiology for years, even decades, to come. The ACR is, and will be, sharing the exciting news with you as we make it happen.

Geraldine B. McGinty, MD, MBA, FACR

Dr. McGinty is chair of the American College of Radiology Board of Chancellors. She is an expert in economics and a passionate advocate for quality imaging and its vital role in the delivery of health care.

Howard B. Fleishon, MD, MMM, FACR

Dr. Fleishon is vice chair of the American College of Radiology Board of Chancellors. He is an expert in government relations and has a special interest in radiology leadership and management.